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IMMM 2017 : The Seventh International Conference on Advances in Information Mining and Management

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Link: http://iaria.org/conferences2017/IMMM17.html
 
When Jun 25, 2017 - Jun 29, 2017
Where Venice, Italy
Submission Deadline Feb 5, 2017
Notification Due Apr 5, 2017
Final Version Due May 12, 2017
Categories    data mining   data management   information retrieval   big data
 

Call For Papers

CALL FOR PAPERS, TUTORIALS, PANELS


IMMM 2017, The Seventh International Conference on Advances in Information Mining and Management

General page: http://www.iaria.org/conferences2017/IMMM17.html

Submission page: http://www.iaria.org/conferences2017/SubmitIMMM17.html


DATASETS 2017, The International Symposium on Designing, Validating, and Using Datasets

General page: http://www.iaria.org/conferences2017/DATASETS.html

Submission page: http://www.iaria.org/conferences2017/DATASETS.html#SubmitAPaper



Event schedule: June 25 - 29, 2017- Venice, Italy


Contributions:

- regular papers [in the proceedings, digital library]

- short papers (work in progress) [in the proceedings, digital library]

- ideas: two pages [in the proceedings, digital library]

- extended abstracts: two pages [in the proceedings, digital library]

- posters: two pages [in the proceedings, digital library]

- posters: slide only [slide-deck posted at www.iaria.org]

- presentations: slide only [slide-deck posted at www.iaria.org]

- demos: two pages [posted at www.iaria.org]

- doctoral forum submissions: [in the proceedings, digital library]


Proposals for:

- mini symposia: see http://www.iaria.org/symposium.html

- workshops: see http://www.iaria.org/workshop.html

- tutorials: [slide-deck posed on www.iaria.org]

- panels: [slide-deck posed on www.iaria.org]


Submission deadline: February 5, 2017


Sponsored by IARIA, www.iaria.org

Extended versions of selected papers will be published in IARIA Journals: http://www.iariajournals.org

Print proceedings will be available via Curran Associates, Inc.: http://www.proceedings.com/9769.html

Articles will be archived in the free access ThinkMind Digital Library: http://www.thinkmind.org


The topics suggested by the conference can be discussed in term of concepts, state of the art, research, standards, implementations, running experiments, applications, and industrial case studies. Authors are invited to submit complete unpublished papers, which are not under review in any other conference or journal in the following, but not limited to, topic areas.

All tracks are open to both research and industry contributions, in terms of Regular papers, Posters, Work in progress, Technical/marketing/business presentations, Demos, Tutorials, and Panels.

Before submission, please check and comply with the editorial rules: http://www.iaria.org/editorialrules.html


IMMM 2017 Topics (for topics and submission details: see CfP on the site)

Call for Papers: http://www.iaria.org/conferences2017/CfPIMMM17.html

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Trends in mining/retrieving/handling data

Big data and Genome Data; Large scale data retrieval; Graph-modeled Data; Geo-tagged photos; Tractable uncertain data; Data curation workflow analysis; Online data integration services; Streaming/real-time/active; Stream processing at scale; Real-time analytics in the same database; Temporal mining; Temporal pattern discovery; Incrementally mining temporal patterns; Keyword search in large networks; Sequence mining with hierarchies; Phonetic time series; Mining communication motifs in dynamic environments; Approximate queries on string collection; Profiling entities; Data-intensive science using scalable analytics; Data-driven discovery; Composite dynamic-and-static indexing; Differential privacy on correlated data; Massive personal time-series clustering; Persistent data sketching; Stream data cleaning; Dynamic event streams; Out-of-Order data streams; Concept-drifting data streams; Indexing metrics for uncertain data; Mining and forecasting of Big time-series Data; Holistic indexing; Crowd mining; Mining subjective properties on the Web; Data semantics and information extraction; Community detection in social networks; Mining and learning activities; Confidence-based and incomplete information

Trends in methodologies/architectures/platforms

Scalable classification frameworks; MapReduce over HybriD Clouds; Parallel Database Systems; Spatio-temporal and textual processing platforms; Deep language embedding; Large-Scale machine learning; Fault-tolerance for parallel data processing; Encrypted query processing; Enforcement of data use policies; Big Data industrial systems; Condensed representation; Temporal graphs; Graph summarization; Subspace and spectral methods; Cross-modal correlations; Open annotation data models; Elastic processing of data streams; Interactive data transformation; On-line aggregation; Interactive analysis on Big Data; Crowdsourcing applications; Distributed online tracking; Social graph partitioning methods; Monitoring of co-evolving data streams; Deep packet inspection systems; Ensemble-based data mining platforms; Sensors-oriented time-series prediction systems; Social multimedia as sensors; Sentiment representation systems

Mining mechanisms and methods

Contextual aggregated information retrieval; Aggregated query for workflows; Data mining algorithms; Media adaptive mining; Agent-based mining; Content-based mining; Context-aware mining; Automation of data extraction; Data mining at a large; Domain-driven data mining; Graph-based data mining; Multilabel information; Multimodal mining; Cloud-based mining; Mining using neurocomputing techniques

Mining support

Querying for mining; Questions for digital investigation; Similarity search; User-generated content; Visualizing data mining; Internationalization and localization techniques for profile/context-based visualization

Type of information mining

Concept mining; Process mining; Concept mining; Knowledge mining; Knowledge discovery; Mining image and video; Mining patterns; Opinion mining; Graph mining; Ontology mining; Semantic annotations and mining; Document mining; Spatial mining; Speech mining; Text mining; Web mining; XML data mining

Pervasive information retrieval

Context and location information retrieval; Mobile information retrieval; Geo-information retrieval; Context-aware information retrieval; Access-driven information retrieval; Location-specific information retrieval; Spacial information retrieval; Semantic-driven retrieval

Automated retrieval and mining

Automated information extraction; Agent-based data mining and information discovery; Agent-based knowledge; Datamining-based agents and multi-agent systems; Agent-mining intelligent applications and systems; Automated retrieval of multimedia streams; Automated retrieval from multimedia archives; Automated copyright infringement detection and watermarking; Automated content summarization; Automatic concept detection, categorization, and genre detection; Automatic speech recognition; Automated cross-media linking

Mining features

Dimensionality reduction; Feature weighting; Subset selection; Feature extraction; Feature construction; Data streams and time series; Selection in high-dimensional domains; Multilingual data mining; Multimedia mining; String processing and data mining; Mining association rules; Mining social relationships; Mining linked data; Mining sequential episodes from time series; Mining time-dependent data; Un-supervised data mining; Semi-structured data; Mining location-sensitive data; Concept-drift in data mining

Information mining and management

Data cleaning; Data updating; Segmentation and clustering; Mining transient information; Warehousing; Web syndication; Data filtering and aggregation; Optimal pruning; Data summarization; Knowledge injection, discovery and classification; Uncertainty removal; Managing incompleteness

Mining from specific sources

Bio data mining; Climate data mining; Data mining in medicine and pharmacology; Data mining in special networks (grids, sensors, etc.); Data management for mobile systems; Data management for sensors; Data mining and management for wireless systems; Dynamic network discovery; Mining from multiple sources; Mining personal semantic data; Mining from social networks; Mining from deep web; Mining from Wikipedia

Data management in special environments

Data management in sensor and mobile ad hoc networks; Data management in mobile peer-to-peer networks; Data management for mobile applications; Data management in mobile/temporal social networks; Management of community sensing/participatory sensing data; Managing pervasive data, sensor data streams and user devices; Managing mobile semantic data; Manging data-intensive mobile computing; Management of real-time data; Managing security data streams; Managing Mobile Web 2.0 data; Managing data in mobile clouds; Data replication, migration and dissemination in mobile environments; Web data processing and security on mobile devices; Resource advertising and discovery techniques

Mining evaluation

Statistics on mining; Ranking of mining results; Provenance; Privacy issues; Patterns for mining; Credibility on data mining; Performance of mining information; Data mining and computational intelligence; Intelligent data understanding; Intelligent data analysis

Mining tools and applications

Data mining applications; Data mining tools and enabling software; Interoperability of information mining tools; Applications for large-scale mining; Content segmentation tools (e.g., shot and semantic scene segmentation); Evaluation methods for TV and radio content analysis tools; Tools for data sets and standard resources


DATASETS 2017 Topics (for topics and submission details: see CfP on the site)

Call for Papers: http://www.iaria.org/conferences2017/DATASETS.html#CallForPapers

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THEORY

The anatomy of designing Datasets

Designing context-based Datasets

Metadata for Datasets

Challenges in designing very large Datasets

Updatable and updating Datasets

Reference Datasets

Datasets families

Repositories of Datasets

Criteria for selecting appropriate Datasets

TYPES

Public and private Datasets

Open Datasets

Big Data and Datasets

Trusted Datasets

Mining massive Datasets

FEATURES

Testing and validating Datasets

Pitfalls with Datasets

Reputation of Datasets

Accuracy estimation of Datasets

Data links in Datasets

APPLICATIONS AND EXPERIMENTS

Context-aware Datasets in the Internet of Things

Datasets for data mining

Datasets used in statistics and machine learning

Online Datasets on collective behavior

Datasets for analytics and knowledge discovery

Regression Datasets

Climate Datasets

Gene Datasets

Health Datasets

Economic Datasets

Social Datasets

Transportation Datasets

Urban Datasets

Education/scholar Datasets


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IMMM 2017 Committee: http://www.iaria.org/conferences2017/ComIMMM17.html

DATASETS 2017 Committee: http://www.iaria.org/conferences2017/DATASETS.html#Committees

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